Evaluation of super-resolution on 50 pancreatic cancer patients with real-time cine MRI from 0.35T MRgRT.

MR-guided radiotherapy (MRgRT) systems provide excellent soft tissue imaging immediately prior to and in real time during radiation delivery for cancer treatment. However, 2D cine MRI often has limited spatial resolution due to high temporal resolution. This work applies a super resolution machine learning framework to 3.5 mm pixel edge length, low resolution (LR), sagittal 2D cine MRI images acquired on a MRgRT system to generate 0.9 mm pixel edge length, super resolution (SR), images originally acquired at 4 frames per second (FPS). LR images were collected from 50 pancreatic cancer patients treated on a ViewRay MR-LINAC. SR images were evaluated using three methods. 1) The first method utilized intrinsic image quality metrics for evaluation. 2) The second used relative metrics including edge detection and structural similarity index (SSIM). 3) Finally, automatically generated tumor contours were created on both low resolution and super resolution images to evaluate target delineation and compared with DICE and SSIM. Intrinsic image quality metrics all had statistically significant improvements for SR images versus LR images, with mean (±1 SD) BRISQUE scores of 29.65 ± 2.98 and 42.48 ± 0.98 for SR and LR, respectively. SR images showed good agreement with LR images in SSIM evaluation, indicating there was not significant distortion of the images. Comparison of LR and SR images with paired high resolution (HR) 3D images showed that SR images had a mean (±1 SD) SSIM value of 0.633 ± 0.063 and LR a value of 0.587 ± 0.067 (p ≪ 0.05). Contours generated on SR images were also more robust to noise addition than those generated on LR images. This study shows that super resolution with a machine learning framework can generate high spatial resolution images from 4fps low spatial resolution cine MRI acquired on the ViewRay MR-LINAC while maintaining tumor contour quality and without significant acquisition or post processing delay.

Big Data Analysis of Media Reports Related to COVID-19.

COVID-19 is lasting longer than expected, which has a huge impact on the economy and on personal life. Each country has a different response method, and the damage scale is also distinct. This study aims to find out how COVID-19-related news was handled in the domestic media to seek ways to minimize the pandemic. The paper focuses on the number of news features by period and by disaster and analyzes related words based on big data. The results of the analysis are as follows. First, in the initial response phase, keywords to identify accurate sources of actual broadcast contents, fake news, social networking service (SNS), etc. were also ranked in the top 20. Second, in the active response phase, when the number of confirmed persons and the government's countermeasures were announced, more than 100 COVID-19-related articles were issued, and the related words increased rapidly from the initial response stage. Therefore, the fact that COVID-19 has been expressed as a keyword indicates that our society is watching with great interest in the government's response to the disease.

Study on the RBE estimation for carbon beam scanning irradiation using a solid-state microdosimeter.

PURPOSE: The purpose of this study was to study the field size effect on the estimated Relative Biological Effectiveness (RBE) for carbon scanning beam irradiation. METHODS: A silicon-on-insulator (SOI) microdosimeter system developed by the Centre for Medical Radiation Physics, University of Wollongong, Australia, was used for lineal-energy measurements (microdosimetric quantity). The RBE values were derived based on the modified microdosimetric kinetic model (MKM) at different depths in a water phantom in the scanning carbon beam for various scanned areas. RESULTS: Our study shows that the difference in RBE values derived from the SOI microdosimeter measurements with the MKM model and from the Treatment Planning System (TPS). The difference of the RBE values is within 6.5 % at the peak point of the spread-out Bragg Peak (SOBP) region. Compared to the spot-beam, RBE values obtained in the scanned-beam with a larger scanned area of 1.0 × 1.0 cm2 have better agreement with which estimated by the TPS. CONCLUSIONS: This study shows the possibility of using the SOI microdosimeter system as a quality assurance (QA) tool for RBE evaluation in carbon-pencil beam scanning radiotherapy.

Clinical Evaluation of Commercial Atlas-Based Auto-Segmentation in the Head and Neck Region.

Background: While atlas segmentation (AS) has proven to be a time-saving and promising method for radiation therapy contouring, optimal methods for its use have not been well-established. Therefore, we investigated the relationship between the size of the atlas patient population and the atlas segmentation auto contouring (AC) performance. Methods: A total of 110 patients' head planning CT images were selected. The mandible and thyroid were selected for this study. The mandibles and thyroids of the patient population were carefully segmented by two skilled clinicians. Of the 110 patients, 100 random patients were registered to 5 different atlas libraries as atlas patients, in groups of 20 to 100, with increments of 20. AS was conducted for each of the remaining 10 patients, either by simultaneous atlas segmentation (SAS) or independent atlas segmentation (IAS). The AS duration of each target patient was recorded. To validate the accuracy of the generated contours, auto contours were compared to manually generated contours (MC) using a volume-overlap-dependent metric, Dice Similarity Coefficient (DSC), and a distance-dependent metric, Hausdorff Distance (HD). Results: In both organs, as the population increased from n = 20 to n = 60, the results showed better convergence. Generally, independent cases produced better performance than simultaneous cases. For the mandible, the best performance was achieved by n = 60 [DSC = 0.92 (0.01) and HD = 6.73 (1.31) mm] and the worst by n = 100 [DSC = 0.90 (0.03) and HD = 10.10 (6.52) mm] atlas libraries. Similar results were achieved with the thyroid; the best performance was achieved by n = 60 [DSC = 0.79 (0.06) and HD = 10.17 (2.89) mm] and the worst by n = 100 [DSC = 0.72 (0.13) and HD = 12.88 (3.94) mm] atlas libraries. Both IAS and SAS showed similar results. Manual contouring of the mandible and thyroid required an average of 1,044 (±170.15) seconds, while AS required an average of 46.4 (±2.8) seconds. Conclusions: The performance of AS AC generally increased as the population of the atlas library increased. However, the performance does not drastically vary in the larger atlas libraries in contrast to the logic that bigger atlas library should lead to better results. In fact, the results do not vary significantly toward the larger atlas library. It is necessary for the institutions to independently research the optimal number of subjects.

Proton-radiography-based quality assurance of proton range compensator.

The aim of this work was to study the feasibility of proton radiography (pRad) as a patient-specific range compensator (RC) quality assurance (QA) tool and to validate its clinical utility by performing QA on RCs having three kinds of possible defects. In order to achieve pRad for a single EBT film, proton beam currents were modulated with new weighting factors, maximizing the linearity of optical-density-to-thickness ratio. Two RCs, examined to be accurately manufactured as planned, were selected to estimate the feasibility of our pRad. The optical densities of the EBT film on which the RC was irradiated with the modulated proton beam were digitized to pixel values (pv) and then converted to thickness using a thickness-pv calibration curve. The thickness information on the pRad was compared with plan data that had been extracted from treatment planning system. The mean thickness difference (TD) over the flat RC regions was calculated as 0.39 mm, and the standard deviation as 0.22 mm, and the proton scattering effect was analyzed by step phantom measurement. Even proton scattering effected a TD of over 1 mm in the large gradient region, the percentage of pixels over the acceptance criterion was only within 1.11% and 3.49%, respectively, when a 1 mm distance to agreement tolerance limit was applied. The QA results for both precisely and imprecisely manufactured RCs demonstrated the high potential utility and clinical applicability of the pRad-based RC QA tool.